1. Technical Field
This disclosure relates to methods of processing digital images and more particularly to methods of processing a digital image for reducing color bleeding effects.
2. Description of the Related Art
Common artifacts introduced by compression algorithms of static or video images based on the discrete cosine transform (DCT) include the so-called block and ringing artifacts. Block artifacts stem from the fact that compression schemes process blocks of an image and consist in visible discontinuities at borders between adjacent blocks. Ringing artifacts consist in distortions and erroneous displaying of borders of objects of the displayed scene.
Both kinds of artifacts occur because a relevant amount of information, carried by the DCT coefficients, is lost in quantization. Block compression plays a role even in the so-called color bleeding.
Color bleedings are distortions of the original image that are present in static images and in the images of video sequences, in the form of color blurring between zones of strong chromatic contrast.
Let us refer to FIG. 1 for better understanding the causes of this phenomenon. The chrominance values of the sixteen input pixels to be processed (FIG. 1a) are decimated with a ratio 2:1 and quantized (FIG. 1b) for obtaining a compressed image. In order to reconstruct an uncompressed image, the pixels of the image of FIG. 1b are dequantized (FIG. 1c) and then interpolated (FIG. 1d).
Chrominance levels of the reconstructed image (FIG. 1d) are substantially different from those of the original image (FIG. 1a) because of the abrupt variation (stepwise) of the chrominance in the original image.
As stated in F. X. Coudoux, M. G. Gazalet, and P. Corlay, “An adaptive post-processing technique for the reduction of color bleeding in DCT coded images,” IEEE Transaction on Circuits Systems for Video Technology, Vol. 14, No. 1 (January 2004), this phenomenon is due to the fact that a quantization and a decimation are executed (essentially in a 4:2:0 subsampling), that introduce spurious information in the reconstructed image.
Examples of color bleeding are evident in a reconstructed image of FIG. 2b (same scene of FIG. 2a), according to the MPEG4 standard, in particular in proximity of the poster and close to the neck of the player, as highlighted in the magnified detail views of FIGS. 2b′ and 2b″. Artifacts of this type are present also in FIGS. 3b and 4b. Recent articles such as F. X. Coudoux, M. G. Gazalet, and P. Corlay, “An adaptive post-processing technique for the reduction of color bleeding in DCT coded images,” IEEE Transaction on Circuits Systems for Video Technology, Vol. 14, No. 1 (January 2004), and F. X. Coudoux, M. G. Gazalet and P. Corlay, “A DCT Domain Postprocessor For Color Bleeding Removal”, Proceedings of the 2005 European Conference on Circuit Theory and Design (2005), propose algorithms for reducing these undesired effects. The image to be elaborated is decomposed in blocks, as depicted in FIG. 5, thus the blocks A B C D potentially affected by color bleeding are identified and their chrominance components Cr and Cb are corrected.
In order to identify image blocks potentially affected by color bleeding, the variances of the chrominance components Cr and Cb and the sharpness of the related luminance block are calculated using a filter for detecting contours of displayed objects, and these values are compared with thresholds. The reason for doing this consists in that color bleeding phenomena occur in correspondence of blocks containing relatively abrupt chrominance and luminance variations.
Undesired effects of color bleeding are eliminated by substituting chrominance components of each block to be corrected (A, B, C, D) with an average of the chrominance components of the surrounding blocks b0, b1, . . . , b7 not affected by color bleeding.
However, these known methods are unable to correct color bleeding effects without sensibly worsening the definition of the contours of the displayed objects. Correcting each pixel simply by averaging chrominance pixels of neighboring blocks reduces color bleeding effects, but at the same time increases the blurring of the contours of displayed objects. This happens because pixels of a block that are differently affected by color bleeding are processed all in the same way. Moreover, the known methods are based on a discrimination among blocks recognized as affected or not by color bleeding, thus in case of an imprecise discrimination they introduce chromatic distortions in blocks originally free of distortion.